Data Science Individual Project 1 - 2024 entry
MODULE TITLE | Data Science Individual Project 1 | CREDIT VALUE | 30 |
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MODULE CODE | COM3022 | MODULE CONVENER | Dr Zeliang Wang (Coordinator) |
DURATION: TERM | 1 | 2 | 3 |
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DURATION: WEEKS | 11 | 11 | 1 |
Number of Students Taking Module (anticipated) | 30 |
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In this module, everything that you have learned in your studies about Computer Science comes together in a substantial individual project. The project is an opportunity to develop your own individual interests in data science and to tackle a substantial research or applied problem. It will involve research into existing techniques and methods for addressing your chosen area, followed by design and implementation of a solution. You will work under the supervision of an experienced academic, and often with a domain expert, who will be able provide guidance and advice.
Pre-requisite Module: COM2013 (Data Science Group Project 2)
This module aims to enable you to consolidate the knowledge, understanding, techniques and skills acquired over the previous two years. It aims to give you the opportunity to research an area of data science or to solve a particular applied problem; usually these will involve the development of a substantial piece of software and analysis. The module involves both initial research into the project area (including the writing of a literature review) and the production of software and analysis addressing the chosen problem.
On successful completion of this module, you should be able to:
Module Specific Skills and Knowledge:
1 Plan a substantial project taking account of foreseeable risks, ethical considerations, etc;
2 Follow a disciplined research and development method in tackling a research and development project;
3 Exercise skills in data science to produce effective software and analysis;
Discipline Specific Skills and Knowledge:
4 Master writing styles appropriate to both a theoretical discursive document and a technical report, including use of tables and figures and good referencing practice;
Personal and Key Transferable/ Employment Skills and Knowledge:
5 Undertake independent research in a chosen topic, summarise findings and provide critical analysis;
6 Impart the results of your work through oral presentation and practical demonstration;
7 Manage your work effectively, with appropriate time planning, attendance at meetings and timely submission of deliverables.
- Students are expected to have weekly meetings with their supervisor and maintain a project log-book which will be handed in along with the final report and assessed as part of the supervisor’s report; log-book entries should record the subjects discussed and actions agreed, and will be signed and dated by both student and supervisor;
- The first formative assessment will cover project scope, risk assessment, ethical considerations, literature review plan, time plan and a list of references;
- The literature review and specification may cover software as well as both printed literature and web sources, all of which must be referenced in a correct and consistent style; at least two pages at the end of the document should take the form of an informal specification of the project making reference to specific technologies or methods informed by the literature review;
- You will give a stand-up presentation to selected peers and staff on the work done so far and plans for future work;
- The final report will cover details of design, implementation, testing and evaluation;
- You will demonstrate the outputs of the project to the two markers and supervisor;
- 10% of the marks for the module will come from your supervisor’s report, which will take into account your progress throughout the year, including attendance at meetings and the oral presentation, submission of agreed deliverables including the log-book, demonstration of ambition and initiative.
Scheduled Learning & Teaching Activities | 16 | Guided Independent Study | 284 | Placement / Study Abroad | 0 |
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Category | Hours of study time | Description |
Scheduled Learning and Teaching | 4 | Lectures, Practicals, Seminars |
Guided Independent Study | 12 | Coursework |
Guided Independent Study | 284 | Self-Study and Background Reading |
Form of Assessment | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Project Statement and Plan | 4 hours | 1 | Oral commentary from supervisor and written feedback using customised marksheet |
Oral Presentation | 20 minutes | 6 | Oral feedback from supervisor and peers |
Coursework | 90 | Written Exams | 0 | Practical Exams | 10 |
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Form of Assessment | % of Credit | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
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Literature Review and Project Specification | 20 | 8 pages | 4, 5 | Written using customised marksheet |
Final Report | 60 | 20 pages | 3-5 | Written using customised marksheet |
Supervisor’s Report | 10 | N/A | 1, 3, 7 | Oral feedback from supervisor |
Demonstration | 10 | 15 minutes | 6 | Written using customised marksheet |
Original Form of Assessment | Form of Re-assessment | ILOs Re-assessed | Time Scale for Re-assessment |
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All Above | Coursework (100%) | All | Completed over summer with a deadline in August |
Re-assessment will be by resubmission of the final report only. For referred candidates, the mark will be capped at 40%. For deferred candidates the mark will be uncapped.
information that you are expected to consult. Further guidance will be provided by the Module Convener
Basic reading:
ELE:
Web based and Electronic Resources:
Other Resources:
Reading list for this module:
CREDIT VALUE | 30 | ECTS VALUE | 15 |
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PRE-REQUISITE MODULES | COM2013 |
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CO-REQUISITE MODULES |
NQF LEVEL (FHEQ) | 6 | AVAILABLE AS DISTANCE LEARNING | No |
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ORIGIN DATE | Friday 12th April 2019 | LAST REVISION DATE | Wednesday 11th September 2024 |
KEY WORDS SEARCH | Project; Literature Review; Data Science; Machine Learning; Statistics; Data Governance; Data Visualisation; Data Exploration |
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Please note that all modules are subject to change, please get in touch if you have any questions about this module.